For SaaS founders
Production RAG assistants, not demos
Documentation search, support deflection, and internal knowledge assistants that answer from your content — deployed, embedded, and monitored.
Start with a paid pilotKhaas builds production RAG (retrieval-augmented generation) assistants for SaaS products — grounded in your own documentation, deployed as an embeddable widget, and behind a five-layer safety pipeline that has handled 13,000+ conversations in production.
Who it’s for: SaaS teams whose support volume or onboarding friction is growing faster than headcount.
See a live RAG assistant
DocsChat is a production RAG widget you can use right now — paste a URL, ask a question, watch it answer from the content.
Open the live DocsChat demoThe problem
- Your team answers the same questions repeatedly while the answers already exist in your docs.
- Off-the-shelf AI chat needs config files, ML knowledge, or custom integration work you don’t have time for.
- Generic chatbots hallucinate because they let the model improvise instead of retrieving grounded answers.
What you get
- Crawl and index your documentation into pgvector, with re-index on demand.
- Schema-constrained Claude responses — the model cannot return malformed data.
- A two-line embeddable widget, iframe-isolated so it never collides with your site’s styling.
- Monitoring, prompt and index tuning, and a monthly performance report on the care retainer.
How I work
Assess → Build → Integrate → Operate
Assess
Audit your docs, data, and tooling. Name the highest-ROI use case before writing code.
Build
Ship the system — deterministic pipeline, grounded retrieval, schema-constrained output.
Integrate
Embed it in your product and workflow. Two-line widget, your branding, your stack.
Operate
Monitor, tune prompts and indexes, update models, and report performance monthly.
Pricing
RAG Pilot
A working assistant on one of your doc sources, plus an evaluation report scoring 100 real support tickets for accuracy — with zero hallucinations on your red-flag set. Credited to the full build if you proceed within 30 days.
Support Deflection System
The complete production RAG assistant across your documentation — deployed, embedded, and answering.
AI Care Retainer
Ongoing monitoring, prompt/index tuning, model updates, and a monthly performance report.
Every build continues on an AI Care Retainer by default. A RAG assistant is not "set and forget" — retrieval drifts as your docs change and models update, so ongoing tuning is what keeps accuracy high after launch.
FAQ
How do we start without committing €18,000 up front?
With a €6,500 RAG Pilot: a working assistant on one of your doc sources plus an accuracy report on 100 real tickets, in 3–4 weeks. It proves the system on your own data, and the fee is credited to the full build if you proceed within 30 days.
Why won’t it hallucinate?
Answers are retrieved from your documentation and the model’s output is schema-constrained. Deterministic retrieval and validation run around the model, not the other way round.
Can I see one working?
Yes — DocsChat is a live RAG widget you can use right now at docschat.khaas.net.